McCambly, H. and Aguilar-Smith, S.: Pork-Barrel Politics and Racialized Transformation?: A Critical Quantitative Study of the Distribution and Use of Federal Academic Earmarks
Principal Investigator(s): View help for Principal Investigator(s) Heather McCambly, University of Pittsburgh
Version: View help for Version V1
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Project Citation:
McCambly, Heather. McCambly, H. and Aguilar-Smith, S.: Pork-Barrel Politics and Racialized Transformation?: A Critical Quantitative Study of the Distribution and Use of Federal Academic Earmarks. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-02-26. https://doi.org/10.3886/E198688V1
Project Description
Summary:
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Paper abstract: Troubled by the inequities in competitive grantmaking, we use critical quantitative methods to analyze the FY2023 federal academic earmarks as a potential mechanism for racialized change work. Specifically, we ask: To what extent does Congress distribute academic earmarks in ways that reinforce or weaken the racialized stratification of resources across organizations in the field? Accordingly, we identify distribution patterns of academic earmarks, considering the allocation of dollars and types of earmarks (i.e., general capacity-building versus specialized grants) across colleges and universities, between white-serving institutions and minority-serving institutions (MSIs), and among MSIs. Based on our analysis, Congress favored a racially reproductive funding portfolio, driven by smaller and more restrictive allocations, not fewer earmarks. However, the distribution of earmarks among MSIs defied normed expectations, as Congress did not privilege whiter, more prestigious MSIs, signaling the potential of pork-barrel politics for racially reparative work.
Data: Merged federal earmarks data for FY2023 and data from the Integrated Postsecondary Data System
Stata dofile: Containing basic analytic processes used in the paper
Data: Merged federal earmarks data for FY2023 and data from the Integrated Postsecondary Data System
Stata dofile: Containing basic analytic processes used in the paper
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